天池比赛 美年健康完整代码

[{"title":"（ 36 个子文件 180.77MB ） 天池比赛 美年健康完整代码","children":[{"title":"美年健康al","children":[{"title":"test_set.csv <span style='color:#111;'> 25.63MB </span>","children":null,"spread":false},{"title":"train_b.csv <span style='color:#111;'> 103.26MB </span>","children":null,"spread":false},{"title":"merge_part1_2.csv <span style='color:#111;'> 128.17MB </span>","children":null,"spread":false},{"title":"lgb权重为1的模型，接下来调lgb内部参量.py <span style='color:#111;'> 9.25KB </span>","children":null,"spread":false},{"title":"results.csv <span style='color:#111;'> 758.20KB </span>","children":null,"spread":false},{"title":"test_b.csv <span style='color:#111;'> 25.56MB </span>","children":null,"spread":false},{"title":"5列全log.py <span style='color:#111;'> 9.44KB </span>","children":null,"spread":false},{"title":"10CV.py <span style='color:#111;'> 11.69KB </span>","children":null,"spread":false},{"title":"TestOfStack.py <span style='color:#111;'> 9.38KB </span>","children":null,"spread":false},{"title":"线性回归单模型.py <span style='color:#111;'> 3.48KB </span>","children":null,"spread":false},{"title":"part_tabid_size.csv <span style='color:#111;'> 28.34KB </span>","children":null,"spread":false},{"title":"meinian_round1_data_part2_20180408.txt <span style='color:#111;'> 152.52MB </span>","children":null,"spread":false},{"title":"2018-5-5(5列都做了log1p).csv <span style='color:#111;'> 624.07KB </span>","children":null,"spread":false},{"title":"岭回归.py <span style='color:#111;'> 3.47KB </span>","children":null,"spread":false},{"title":"train_set.csv <span style='color:#111;'> 103.26MB </span>","children":null,"spread":false},{"title":"[new] meinian_round1_test_a_20180409.csv <span style='color:#111;'> 363.33KB </span>","children":null,"spread":false},{"title":"xgb单模型.py <span style='color:#111;'> 3.54KB </span>","children":null,"spread":false},{"title":"结巴分词用于切分文本.py <span style='color:#111;'> 3.85KB </span>","children":null,"spread":false},{"title":"xgboost的0134列与xgboost和LGNBM的2.py <span style='color:#111;'> 3.93KB </span>","children":null,"spread":false},{"title":"模型融合.py <span style='color:#111;'> 3.79KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"tmp.csv <span style='color:#111;'> 293.92MB </span>","children":null,"spread":false},{"title":"数据清洗 豆腐代码.py <span style='color:#111;'> 6.71KB </span>","children":null,"spread":false},{"title":"v1.py <span style='color:#111;'> 1.98KB </span>","children":null,"spread":false},{"title":"submission.csv <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"数据清洗v1.py <span style='color:#111;'> 6.70KB </span>","children":null,"spread":false},{"title":"meinian_round1_data_part1_20180408.txt <span style='color:#111;'> 289.85MB </span>","children":null,"spread":false},{"title":"test_.csv <span style='color:#111;'> 25.63MB </span>","children":null,"spread":false},{"title":"xgb模型.py <span style='color:#111;'> 3.42KB </span>","children":null,"spread":false},{"title":"train_.csv <span style='color:#111;'> 103.26MB </span>","children":null,"spread":false},{"title":"xgboost与lgb调参得出最佳的为lgb权重为1.py <span style='color:#111;'> 9.76KB </span>","children":null,"spread":false},{"title":"数据处理v3.1.py <span style='color:#111;'> 3.77KB </span>","children":null,"spread":false},{"title":"datas.csv <span style='color:#111;'> 65.95MB </span>","children":null,"spread":false},{"title":"随机森林求最佳参数.py <span style='color:#111;'> 9.30KB </span>","children":null,"spread":false},{"title":"More_features.py <span style='color:#111;'> 11.29KB </span>","children":null,"spread":false},{"title":"meinian_round1_train_20180408.csv <span style='color:#111;'> 2.02MB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]